class_docstr: Guided-Anchor-based RetinaNet head.
docstr: Initialize weights of the layer.
docstr_tok: ["Initialize","weights","of","the","layer","."]
code: def init_weights(self):
      """Initialize weights of the layer."""
      for m in self.cls_convs:
          normal_init(m.conv, std=0.01)
      for m in self.reg_convs:
          normal_init(m.conv, std=0.01)
  
      self.feature_adaption_cls.init_weights()
      self.feature_adaption_reg.init_weights()
  
      bias_cls = bias_init_with_prob(0.01)
      normal_init(self.conv_loc, std=0.01, bias=bias_cls)
      normal_init(self.conv_shape, std=0.01)
      normal_init(self.retina_cls, std=0.01, bias=bias_cls)
      normal_init(self.retina_reg, std=0.01)
  
file_path: insightface/detection/scrfd/mmdet/models/dense_heads/ga_retina_head.py
imports: import torch.nn
  from mmcv.cnn import ConvModule, bias_init_with_prob, normal_init
  from mmcv.ops import MaskedConv2d
  from ..builder import HEADS
  from .guided_anchor_head import FeatureAdaption, GuidedAnchorHead
label_desc: Use image node_id 3 for calling the GARetinaHead obj's underlying member method code with example usage: obj.init_weights() without return types